Optical character recognition (OCR) systems are employed in many fields and settings to identify characters within one or more images. For example, optical character recognition is commonly implemented for license plate recognition.
While known OCR systems are often capable of generating accurate recognition results when the characters being identified appear prominently and clearly within the images being processed, such systems are far less accurate when processing images of sub-optimal quality. For instance, it can be appreciated that many common scenarios can arise that result in an image (such as an image of a license plate) being distorted in one or more ways (due to the effects of motion, lighting inconsistencies, etc.). As such, existing OCR systems are frequently faced with distorted images that such systems are unable to process accurately. In such situations, these systems either a) process such images inaccurately or b) abstain from processing such images (thereby requiring either a human operator to perform manual recognition of the image, or else not performing any recognition of the image).
It is with respect to these and other considerations that the disclosure made herein is presented.